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Title: GitHub - freecamel/GenerativeModel: https://github.com/hindupuravinash/the-gan-zoo

Open Graph Title: GitHub - freecamel/GenerativeModel: https://github.com/hindupuravinash/the-gan-zoo

X Title: GitHub - freecamel/GenerativeModel: https://github.com/hindupuravinash/the-gan-zoo

Description: https://github.com/hindupuravinash/the-gan-zoo. Contribute to freecamel/GenerativeModel development by creating an account on GitHub.

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herehttps://github.com/hindupuravinash/the-gan-zoo/blob/master/gans.tsv
Deep Hunthttps://deephunt.in
blogposthttps://medium.com/deep-hunt/the-gan-zoo-79597dc8c347
Twitterhttps://www.twitter.com/hindupuravinash
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modelinghttps://arxiv.org/abs/1610.07584
githubhttps://github.com/zck119/3dgan-release
Improved Adversarial Systems for 3D Object Generation and Reconstructionhttps://arxiv.org/abs/1707.09557
githubhttps://github.com/EdwardSmith1884/3D-IWGAN
3D Object Reconstruction from a Single Depth View with Adversarial Learninghttps://arxiv.org/abs/1708.07969
githubhttps://github.com/Yang7879/3D-RecGAN
ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networkshttps://drive.google.com/file/d/0B3wEP_lEl0laVTdGcHE2VnRiMlE/view
githubhttps://github.com/IgorSusmelj/ABC-GAN
Conditional Image Synthesis With Auxiliary Classifier GANshttps://arxiv.org/abs/1610.09585
Face Aging With Conditional Generative Adversarial Networkshttps://arxiv.org/abs/1702.01983
AdaGAN: Boosting Generative Modelshttps://arxiv.org/abs/1701.02386v1
AE-GAN: adversarial eliminating with GANhttps://arxiv.org/abs/1707.05474
Learning Inverse Mapping by Autoencoder based Generative Adversarial Netshttps://arxiv.org/abs/1703.10094
Amortised MAP Inference for Image Super-resolutionhttps://arxiv.org/abs/1610.04490
Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layoutshttps://arxiv.org/abs/1612.00215
Adversarially Learned Inferencehttps://arxiv.org/abs/1606.00704
AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networkshttps://arxiv.org/abs/1707.01400
Activation Maximization Generative Adversarial Netshttps://arxiv.org/abs/1703.02000
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discoveryhttps://arxiv.org/abs/1703.05921v1
Adversarially Regularized Autoencoders for Generating Discrete Structureshttps://arxiv.org/abs/1706.04223
githubhttps://github.com/jakezhaojb/ARAE
Adversarial Representation Learning for Domain Adaptationhttps://arxiv.org/abs/1707.01217
ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Networkhttps://arxiv.org/abs/1709.00938
ArtGAN: Artwork Synthesis with Conditional Categorial GANshttps://arxiv.org/abs/1702.03410
Generative Adversarial Nets from a Density Ratio Estimation Perspectivehttps://arxiv.org/abs/1610.02920
Deep and Hierarchical Implicit Modelshttps://arxiv.org/abs/1702.08896
Bayesian GANhttps://arxiv.org/abs/1705.09558
Bayesian Conditional Generative Adverserial Networkshttps://arxiv.org/abs/1706.05477
BEGAN: Boundary Equilibrium Generative Adversarial Networkshttps://arxiv.org/abs/1703.10717
Binary Generative Adversarial Networks for Image Retrievalhttps://arxiv.org/abs/1708.04150
githubhttps://github.com/htconquer/BGAN
Adversarial Feature Learninghttps://arxiv.org/abs/1605.09782v7
Boundary-Seeking Generative Adversarial Networkshttps://arxiv.org/abs/1702.08431v1
C-RNN-GAN: Continuous recurrent neural networks with adversarial traininghttps://arxiv.org/abs/1611.09904
githubhttps://github.com/olofmogren/c-rnn-gan/
CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networkshttps://arxiv.org/abs/1705.02355
githubhttps://github.com/hep-lbdl/CaloGAN
CAN: Creative Adversarial Networks, Generating Art by Learning About Styles and Deviating from Style Normshttps://arxiv.org/abs/1706.07068
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networkshttps://arxiv.org/abs/1511.06390v2
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Traininghttps://arxiv.org/abs/1709.02023
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networkshttps://arxiv.org/abs/1611.06430
githubhttps://github.com/edenton/cc-gan
Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Networkhttps://arxiv.org/abs/1708.09105
Conditional Generative Adversarial Netshttps://arxiv.org/abs/1411.1784
Controllable Generative Adversarial Networkhttps://arxiv.org/abs/1708.00598
An Online Learning Approach to Generative Adversarial Networkshttps://arxiv.org/abs/1706.03269
CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learninghttps://arxiv.org/abs/1710.05106
Coupled Generative Adversarial Networkshttps://arxiv.org/abs/1606.07536v2
Conditional CycleGAN for Attribute Guided Face Image Generationhttps://arxiv.org/abs/1705.09966
Generative Semantic Manipulation with Contrasting GANhttps://arxiv.org/abs/1708.00315
Contextual RNN-GANs for Abstract Reasoning Diagram Generationhttps://arxiv.org/abs/1609.09444
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fieldshttps://arxiv.org/abs/1708.08819
The Cramer Distance as a Solution to Biased Wasserstein Gradientshttps://arxiv.org/abs/1705.10743
Channel-Recurrent Variational Autoencodershttps://arxiv.org/abs/1706.03729
Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Netshttps://arxiv.org/abs/1703.04887
CVAE-GAN: Fine-Grained Image Generation through Asymmetric Traininghttps://arxiv.org/abs/1703.10155
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkshttps://arxiv.org/abs/1703.10593
githubhttps://github.com/junyanz/CycleGAN
Dual Discriminator Generative Adversarial Netshttp://arxiv.org/abs/1709.03831
Distributional Adversarial Networkshttps://arxiv.org/abs/1706.09549
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkshttps://arxiv.org/abs/1511.06434
githubhttps://github.com/Newmu/dcgan_code
DeLiGAN : Generative Adversarial Networks for Diverse and Limited Datahttps://arxiv.org/abs/1706.02071
githubhttps://github.com/val-iisc/deligan
Learning to Discover Cross-Domain Relations with Generative Adversarial Networkshttps://arxiv.org/abs/1703.05192v1
One-Sided Unsupervised Domain Mappinghttps://arxiv.org/abs/1706.00826
Dual Motion GAN for Future-Flow Embedded Video Predictionhttps://arxiv.org/abs/1708.00284
Representation Learning by Rotating Your Faceshttps://arxiv.org/abs/1705.11136
How to Train Your DRAGANhttps://arxiv.org/abs/1705.07215
githubhttps://github.com/kodalinaveen3/DRAGAN
Depth Structure Preserving Scene Image Generationhttps://arxiv.org/abs/1706.00212
Unsupervised Cross-Domain Image Generationhttps://arxiv.org/abs/1611.02200
DualGAN: Unsupervised Dual Learning for Image-to-Image Translationhttps://arxiv.org/abs/1704.02510v1
Dualing GANshttps://arxiv.org/abs/1706.06216
Energy-based Generative Adversarial Networkhttps://arxiv.org/abs/1609.03126v4
Stabilizing Training of Generative Adversarial Networks through Regularizationhttps://arxiv.org/abs/1705.09367
Enhanced Experience Replay Generation for Efficient Reinforcement Learninghttps://arxiv.org/abs/1705.08245
ExprGAN: Facial Expression Editing with Controllable Expression Intensityhttps://arxiv.org/abs/1709.03842
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimizationhttps://arxiv.org/abs/1606.00709
Towards Large-Pose Face Frontalization in the Wildhttps://arxiv.org/abs/1704.06244
Synthesizing Filamentary Structured Images with GANshttps://arxiv.org/abs/1706.02185
Fisher GANhttps://arxiv.org/abs/1705.09675
Flow-GAN: Bridging implicit and prescribed learning in generative modelshttps://arxiv.org/abs/1705.08868
Generative Adversarial Mapping Networkshttps://arxiv.org/abs/1709.09820
Generative Adversarial Networkshttps://arxiv.org/abs/1406.2661
githubhttps://github.com/goodfeli/adversarial
Generative Adversarial Text to Image Synthesishttps://arxiv.org/abs/1605.05396
githubhttps://github.com/reedscot/icml2016
GANs for Biological Image Synthesishttps://arxiv.org/abs/1708.04692
githubhttps://github.com/aosokin/biogans
Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faceshttps://arxiv.org/abs/1708.02681
Deep Generative Adversarial Networks for Compressed Sensing Automates MRIhttps://arxiv.org/abs/1706.00051
Context-Aware Generative Adversarial Privacyhttps://arxiv.org/abs/1710.09549
Learning What and Where to Drawhttps://arxiv.org/abs/1610.02454
githubhttps://github.com/reedscot/nips2016
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Datahttps://arxiv.org/abs/1705.04932
githubhttps://github.com/Prinsphield/GeneGAN
Geometric GANhttps://arxiv.org/abs/1705.02894
Generative Multi-Adversarial Networkshttp://arxiv.org/abs/1611.01673
Towards Understanding the Dynamics of Generative Adversarial Networkshttps://arxiv.org/abs/1706.09884
Gang of GANs: Generative Adversarial Networks with Maximum Margin Rankinghttps://arxiv.org/abs/1704.04865
GP-GAN: Towards Realistic High-Resolution Image Blendinghttps://arxiv.org/abs/1703.07195
githubhttps://github.com/wuhuikai/GP-GAN
GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarkshttps://arxiv.org/abs/1710.00962
Generating images with recurrent adversarial networkshttps://arxiv.org/abs/1602.05110
githubhttps://github.com/jiwoongim/GRAN
Neural Photo Editing with Introspective Adversarial Networkshttps://arxiv.org/abs/1609.07093
githubhttps://github.com/ajbrock/Neural-Photo-Editor
Invertible Conditional GANs for image editinghttps://arxiv.org/abs/1611.06355
githubhttps://github.com/Guim3/IcGAN
Image De-raining Using a Conditional Generative Adversarial Networkhttps://arxiv.org/abs/1701.05957v3
Generative Visual Manipulation on the Natural Image Manifoldhttps://arxiv.org/abs/1609.03552v2
githubhttps://github.com/junyanz/iGAN
Improved Techniques for Training GANshttps://arxiv.org/abs/1606.03498
githubhttps://github.com/openai/improved-gan
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Netshttps://arxiv.org/abs/1606.03657v1
githubhttps://github.com/openai/InfoGAN
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval modelshttps://arxiv.org/abs/1705.10513v1
On Unifying Deep Generative Modelshttps://arxiv.org/abs/1706.00550
Representation Learning and Adversarial Generation of 3D Point Cloudshttps://arxiv.org/abs/1707.02392
Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesishttps://arxiv.org/abs/1701.05927
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networkshttps://arxiv.org/abs/1506.05751
githubhttps://github.com/facebook/eyescream
Linear Discriminant Generative Adversarial Networkshttps://arxiv.org/abs/1707.07831
Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Imageshttps://arxiv.org/abs/1709.01993
Long Text Generation via Adversarial Training with Leaked Informationhttps://arxiv.org/abs/1709.08624
Likelihood Estimation for Generative Adversarial Networkshttps://arxiv.org/abs/1707.07530
LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generationhttps://arxiv.org/abs/1703.01560v1
Loss-Sensitive Generative Adversarial Networks on Lipschitz Densitieshttps://arxiv.org/abs/1701.06264
Least Squares Generative Adversarial Networkshttps://arxiv.org/abs/1611.04076v3
Multi-Agent Diverse Generative Adversarial Networkshttps://arxiv.org/abs/1704.02906
MAGAN: Margin Adaptation for Generative Adversarial Networkshttps://arxiv.org/abs/1704.03817v1
Generating Adversarial Malware Examples for Black-Box Attacks Based on GANhttps://arxiv.org/abs/1702.05983v1
Maximum-Likelihood Augmented Discrete Generative Adversarial Networkshttps://arxiv.org/abs/1702.07983
Deep Unsupervised Representation Learning for Remote Sensing Imageshttps://arxiv.org/abs/1612.08879
McGan: Mean and Covariance Feature Matching GANhttps://arxiv.org/abs/1702.08398v1
Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networkshttps://arxiv.org/abs/1709.07592
Mode Regularized Generative Adversarial Networkshttps://arxiv.org/abs/1612.02136
Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networkshttps://arxiv.org/abs/1703.06490v1
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networkshttps://arxiv.org/abs/1604.04382
githubhttps://github.com/chuanli11/MGANs
Multi-Generator Generative Adversarial Netshttps://arxiv.org/abs/1708.02556
Generalization and Equilibrium in Generative Adversarial Nets (GANs)https://arxiv.org/abs/1703.00573v3
MMD GAN: Towards Deeper Understanding of Moment Matching Networkhttps://arxiv.org/abs/1705.08584
githubhttps://github.com/dougalsutherland/opt-mmd
MMGAN: Manifold Matching Generative Adversarial Network for Generating Imageshttps://arxiv.org/abs/1707.08273
MoCoGAN: Decomposing Motion and Content for Video Generationhttps://arxiv.org/abs/1707.04993
githubhttps://github.com/sergeytulyakov/mocogan
Message Passing Multi-Agent GANshttps://arxiv.org/abs/1612.01294
MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networkshttps://arxiv.org/abs/1709.06298
Multi-view Generative Adversarial Networkshttps://arxiv.org/abs/1611.02019v1
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learninghttps://arxiv.org/abs/1709.06683
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models https://arxiv.org/abs/1705.10843
Perceptual Adversarial Networks for Image-to-Image Transformationhttps://arxiv.org/abs/1706.09138
PassGAN: A Deep Learning Approach for Password Guessinghttps://arxiv.org/abs/1709.00440
Perceptual Generative Adversarial Networks for Small Object Detectionhttps://arxiv.org/abs/1706.05274
Probabilistic Generative Adversarial Networkshttps://arxiv.org/abs/1708.01886
Image-to-Image Translation with Conditional Adversarial Networkshttps://arxiv.org/abs/1611.07004
githubhttps://github.com/phillipi/pix2pix
PixelGAN Autoencodershttps://arxiv.org/abs/1706.00531
The Pose Knows: Video Forecasting by Generating Pose Futureshttps://arxiv.org/abs/1705.00053
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Spacehttps://arxiv.org/abs/1612.00005
3D Shape Induction from 2D Views of Multiple Objectshttps://arxiv.org/abs/1612.05872
Learning Texture Manifolds with the Periodic Spatial GANhttp://arxiv.org/abs/1705.06566
Adversarial Ranking for Language Generation https://arxiv.org/abs/1705.11001
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANshttps://arxiv.org/abs/1706.02633
Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networkshttps://arxiv.org/abs/1709.00753
RenderGAN: Generating Realistic Labeled Datahttps://arxiv.org/abs/1611.01331
Generative Adversarial Network based on Resnet for Conditional Image Restorationhttps://arxiv.org/abs/1707.04881
Language Generation with Recurrent Generative Adversarial Networks without Pre-traininghttps://arxiv.org/abs/1706.01399
githubhttps://github.com/amirbar/rnn.wgan
Stabilizing GAN Training with Multiple Random Projectionshttps://arxiv.org/abs/1705.07831
githubhttps://github.com/ayanc/rpgan
Recurrent Topic-Transition GAN for Visual Paragraph Generationhttps://arxiv.org/abs/1703.07022v2
Relaxed Wasserstein with Applications to GANshttps://arxiv.org/abs/1705.07164
SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networkshttps://arxiv.org/abs/1611.08788v1
SalGAN: Visual Saliency Prediction with Generative Adversarial Networkshttps://arxiv.org/abs/1701.01081
githubhttps://github.com/imatge-upc/saliency-salgan-2017
From source to target and back: symmetric bi-directional adaptive GANhttps://arxiv.org/abs/1705.08824
Semantically Decomposing the Latent Spaces of Generative Adversarial Networkshttps://arxiv.org/abs/1705.07904
SEGAN: Speech Enhancement Generative Adversarial Networkhttps://arxiv.org/abs/1703.09452v1
SeGAN: Segmenting and Generating the Invisiblehttps://arxiv.org/abs/1703.10239
SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentationhttps://arxiv.org/abs/1706.01805
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradienthttps://arxiv.org/abs/1609.05473v5
githubhttps://github.com/LantaoYu/SeqGAN
Texture Synthesis with Spatial Generative Adversarial Networkshttps://arxiv.org/abs/1611.08207
Stacked Generative Adversarial Networkshttps://arxiv.org/abs/1612.04357v4
githubhttps://github.com/xunhuang1995/SGAN
Steganographic Generative Adversarial Networkshttps://arxiv.org/abs/1703.05502
Learning from Simulated and Unsupervised Images through Adversarial Traininghttps://arxiv.org/abs/1612.07828
Adversarial Training For Sketch Retrievalhttps://arxiv.org/abs/1607.02748
Semi-Latent GAN: Learning to generate and modify facial images from attributeshttps://arxiv.org/abs/1704.02166
Spectral Normalization for Generative Adversarial Networkshttps://drive.google.com/file/d/0B8HZ50DPgR3eSVV6YlF3XzQxSjQ/view
githubhttps://github.com/pfnet-research/chainer-gan-lib
Softmax GANhttps://arxiv.org/abs/1704.06191
Class-Splitting Generative Adversarial Networkshttps://arxiv.org/abs/1709.07359
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkhttps://arxiv.org/abs/1609.04802
Semi-supervised Conditional GANshttps://arxiv.org/abs/1708.05789
Guiding InfoGAN with Semi-Supervisionhttps://arxiv.org/abs/1707.04487
SSGAN: Secure Steganography Based on Generative Adversarial Networkshttps://arxiv.org/abs/1707.01613
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networkshttps://arxiv.org/abs/1611.06430v1
Style Transfer Generative Adversarial Networks: Learning to Play Chess Differentlyhttps://arxiv.org/abs/1702.06762
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networkshttps://arxiv.org/abs/1612.03242v1
Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLEhttps://arxiv.org/abs/1707.00797
Generative Image Modeling using Style and Structure Adversarial Networkshttps://arxiv.org/abs/1603.05631v2
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Networkhttps://arxiv.org/abs/1703.06412v2
githubhttps://github.com/dashayushman/TAC-GAN
Outline Colorization through Tandem Adversarial Networkshttps://arxiv.org/abs/1704.08834
TextureGAN: Controlling Deep Image Synthesis with Texture Patcheshttps://arxiv.org/abs/1706.02823
Temporal Generative Adversarial Netshttps://arxiv.org/abs/1611.06624v1
Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesishttps://arxiv.org/abs/1704.04086
Triple Generative Adversarial Netshttps://arxiv.org/abs/1703.02291v2
Unrolled Generative Adversarial Networkshttps://arxiv.org/abs/1611.02163
githubhttps://github.com/poolio/unrolled_gan
Autoencoding beyond pixels using a learned similarity metrichttps://arxiv.org/abs/1512.09300
Multi-View Image Generation from a Single-Viewhttps://arxiv.org/abs/1704.04886
Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networkshttps://arxiv.org/abs/1704.00849
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learninghttps://arxiv.org/abs/1705.07761
githubhttps://github.com/akashgit/VEEGAN
Generating Videos with Scene Dynamicshttps://arxiv.org/abs/1609.02612
githubhttps://github.com/cvondrick/videogan
Generative Adversarial Networks as Variational Training of Energy Based Modelshttps://arxiv.org/abs/1611.01799
githubhttps://github.com/Shuangfei/vgan
Image Generation and Editing with Variational Info Generative Adversarial Networkshttps://arxiv.org/abs/1701.04568v1
VIGAN: Missing View Imputation with Generative Adversarial Networkshttps://arxiv.org/abs/1708.06724
Variance Regularizing Adversarial Learninghttps://arxiv.org/abs/1707.00309
WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Imageshttps://arxiv.org/abs/1702.07392v1
Wasserstein GANhttps://arxiv.org/abs/1701.07875v2
githubhttps://github.com/martinarjovsky/WassersteinGAN
Improved Training of Wasserstein GANshttps://arxiv.org/abs/1704.00028
githubhttps://github.com/igul222/improved_wgan_training
Weakly Supervised Generative Adversarial Networks for 3D Reconstruction https://arxiv.org/abs/1705.10904
Variational Approaches for Auto-Encoding Generative Adversarial Networkshttps://arxiv.org/abs/1706.04987
githubhttps://github.com/victor-shepardson/alpha-GAN
Triangle Generative Adversarial Networkshttps://arxiv.org/abs/1709.06548
https://github.com/hindupuravinash/the-gan-zoohttps://github.com/hindupuravinash/the-gan-zoo
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